Causal Bounds

This repository contains the implementation and experiments for my Bachelor's Thesis: "Bounding Causal Effects and Counterfactuals".

🚀 Quick Start

Running Algorithms

For a comfortable way to run the algorithms, I recommend using my Python package:

CausalBoundingEngine

Recreating Thesis Experiments

To reproduce the experiments from my thesis, follow these steps:

Prerequisites

• Python with all required dependencies
• R programming language
• Java

Running Simulations

1. Core Scenarios: Use the main simulation script

   python run_all_simulations.py 2000 --R_path "/usr/lib/R"

2. Binary Entropy Confounding: Use the specialized entropy simulation

   python run_entropy_simulation.py 2000 --R_path "/usr/lib/R"

Both scripts are located in the simulation_engine folder.

Parameters:

• First argument: Number of simulations (I used 2000 for thesis results)
• --R_path: Path to your R installation

Analyzing Results

To generate bound statistics tables, use:

from simulation_engine.util.plotting_util import print_bound_statistics_table
print_bound_statistics_table()

Running the Classifier (Random Forest)

1. Navigate to the classification/ folder.
2. Run the classification.ipynb notebook.

📁 Repository Structure

• simulation_engine/: Main simulation scripts and utilities
• Other folders: Experimental code and result analysis tools

📊 Results

The simulation results and analysis tools are included in various folders throughout the repository for exploring algorithm performance and bound quality.

📚 References

This repository implements algorithms from the following research works:

• Manski (1990) - Nonparametric bounds foundation
• Tian & Pearl (2000) - Probability of causation bounds
• Duarte et al. (2023) - Autobound optimization approach
• Jiang & Shpitser (2020) - Entropy-based weak confounding
• Sachs et al. (2022) - Causaloptim R library
• Zaffalon et al. (2022) - Causal expectation maximisation approach
• Zhang & Bareinboim (2021) - Continuous outcome bounding

For detailed references and citations, please consult:

• The thesis PDF document
• CausalBoundingEngine documentation